1. Field of the Invention
The present invention relates to a feature point positioning apparatus, image recognition apparatus, processing method thereof and computer-readable storage medium.
2. Description of the Related Art
A technique for recognizing a predetermined pattern from image data (for example, face recognition) is known. In such recognition processing, position decisions of face organs or feature portions associated with them (to be referred to as feature points hereinafter) are important tasks, and often limit a recognition performance.
The high-precision position decisions of feature points require a heavy processing load, and often limit the time required for the overall recognition processing. Japanese Patent Laid-Open No. 2009-75999 (to be referred to as Reference 1) discloses a method of reducing the number of feature points to be extracted from a frame to be processed using the recognition result of the previous frame when an individual is to be recognized from moving image data. That is, once a target person has been recognized (tracking state), the number of feature points to be extracted in the next frame is reduced, thus speeding up the processing. On the other hand, [Beumer, G. M.; Tao, Q.; Bazen, A. M.; Veldhuis, R. N. J. “A landmark paper in face recognition” Automatic Face and Gesture Recognition, 2006. FGR 2006. 7th International Conference, pp. 73-78 (to be referred to as Reference 2 hereinafter)] discloses a method of deciding a plurality of face organ feature positions according to geometrical restrictions.
Since the method disclosed in Reference 1 reduces the number of feature points, a recognition performance drop is considerable. Upon reducing feature points, a load is imposed on recognition processing to be executed using the reduced feature points. For example, in the recognition processing, a plurality of recognition processing methods and parameters (various processing parameters, registered data, etc. used in recognition) have to be prepared, and an arbitrary method and parameters have to be selected from them. For this reason, as a result of replacing and selecting parameters, a processing time and memory resources required for processing increase.
With the method disclosed in Reference 2, the positions of feature points are corrected using a subspace. However, when the number of target feature points is changed, subspaces have to be prepared in correspondence with the numbers of feature points.